In recent years, with the development of bearer technologies, users impose higher and higher requirements on the coding quality of the audio coder. While pursuing voice conversation, users expect to obtain higher quality and richer media services. On the one hand, in the communications field, users are not satisfied with the quality of the narrowband voice codec at all. Broadband and ultra-broadband voice coders and decoders are phased in. On the other hand, the audio coder applied in the multimedia technical field strives to provide audio coding characterized by low rates and high quality.
Currently, most of the standardized audio coders encode signals by combining the transform coding technology, the psychoacoustic model, and the lattice vector quantization technology.
In the prior art, the latest embedded variable-rate coder put forward by the International Telecommunication Union Telecommunication Standardization Sector (ITU-T) in G.718 uses a lattice codebook index coding method based on hierarchical combination. The coding process includes: encoding a sign of a vector to be coded, and obtaining a modulus vector corresponding to the vector to be coded; and removing corresponding elements in the modulus vector to be coded consecutively according to pre-stored vectors (namely, a vector that represents value of a removed element on each layer and corresponds to each leader vector, and a hierarchical combined coding parameter vector that represents the number of bits required for encoding the sign, the number of layers in the hierarchical coding, and the number of dimensions of the modulus vector on each layer except the top layer); encoding the position of each remaining element on the upper layer; accumulating the coding values on all layers; and obtaining an index value of the final vector to be coded in view of the contribution of the sign coding value of the vector to be coded.
However, the solution above increases the storage complexity. Especially for the lattice vector quantizer characterized by large number of bits to be coded and many leader codewords, the increased storage complexity is almost equivalent to the storage complexity of the codebook itself.